Multimodality multi-lead ECG arrhythmia classification using self-supervised learning

T Phan, D Le, P Brijesh, D Adjeroh, J Wu… - 2022 IEEE-EMBS …, 2022 - ieeexplore.ieee.org
Electrocardiogram (ECG) signal is one of the most effective sources of information mainly
employed for the diagnosis and prediction of cardiovascular diseases (CVDs) connected …

A study of engine room smoke detection based on proactive machine vision model for intelligent ship

P Zhang, Z Song, C Li, Y Liu, Y Zou, Y Zhang… - Expert Systems with …, 2024 - Elsevier
Fire disaster causes damage to ships, pollute the environment, and threatens people's lives,
so making early detection and reasonable decision is essential for avoiding catastrophic …

Enhancing medical image object detection with collaborative multi-agent deep Q-networks and multi-scale representation

Q Wang, F Liu, R Zou, Y Wang, C Zheng, Z Tian… - EURASIP Journal on …, 2023 - Springer
Object detection holds a crucial role in medical diagnostics. Tasks like organ segmentation
and malignancy diagnosis typically necessitate preliminary localization of corresponding …

A Survey From Distributed Machine Learning to Distributed Deep Learning

M Dehghani, Z Yazdanparast - arXiv preprint arXiv:2307.05232, 2023 - arxiv.org
Artificial intelligence has achieved significant success in handling complex tasks in recent
years. This success is due to advances in machine learning algorithms and hardware …

SolarFormer: Multi-scale transformer for solar PV profiling

A De Luis, M Tran, T Hanyu, A Tran… - … on Smart Grid …, 2024 - ieeexplore.ieee.org
As climate change intensifies, the global imperative to shift towards sustainable energy
sources becomes more pronounced. Photovoltaic (PV) energy is a favored choice due to its …

Double graph attention networks for visual semantic navigation

Y Lyu, MS Talebi - Neural Processing Letters, 2023 - Springer
Artificial Intelligence (AI) based on knowledge graphs has been invested in realizing human
intelligence like thinking, learning, and logical reasoning. It is a great promise to make AI …

Unlabeled learning algorithms and operations: overview and future trends in defense sector

E e Oliveira, M Rodrigues, JP Pereira… - Artificial Intelligence …, 2024 - Springer
In the defense sector, artificial intelligence (AI) and machine learning (ML) have been used
to analyse and decipher massive volumes of data, namely for target recognition …

High-resolution recognition of FOAM modes via an improved EfficientNet V2 based convolutional neural network

Y Shi, Z Ma, H Chen, Y Ke, Y Chen, X Zhou - Frontiers of Physics, 2024 - Springer
Vortex beam with fractional orbital angular momentum (FOAM) is the excellent candidate for
improving the capacity of free-space optical (FSO) communication system due to its infinite …

Environmental Intelligent Perception in the Industrial Internet of Things: A Case Study Analysis of a Multi-crane Visual Sorting System

M Fu, Z Wang, J Wang, Q Wang, J Wu… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Future environmental perception (EP) in the Industrial Internet of Things (IIoT) is expected to
interconnect massive sensing objects, merge various intelligent technologies, and efficiently …

Genes in Intelligent Agents

F Feng, J Wang, C Zhang, W Li, X Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
Training intelligent agents in Reinforcement Learning (RL) is much more time-consuming
than animal learning. This is because agents learn from scratch, but animals learn with …